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With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
Visit our Blogs & News portal or check out our recent posts below.
GDPR in Europe. State-by-state data privacy laws in the U.S. Online businesses which got their start in dorm rooms and garages have entered every arena including grocery, health, and politics. Social media habits are no longer in the purview of angsty teens, but are in high demand by corporations; reaching to the highest office in this land. Data infuses every business, day-to-day life, and personal preference, but has it been the grand design imagined at the turn of this century? We can speak with people around the world in real-time, but the internet and the data it gathers has raised a curtain we can hide behind. What had once been intended to unite us, had alienated us instead. As we enter a new decade, it begs the question. Can the new decade bring what the last decade missed? Grand Statements Distract from the Bigger Picture Somewhere between the Y2K scare and the predictions of a digital age, tendrils of the then superhighway began to weave itself into our daily lives. Shouting its pros from the rooftops, and little to nothing of the cons, we became apathetic to our own sensibilities. We put our faith in tech, expecting it to tame the wild side of the possibilities within the internet’s environment. It didn’t. We held grandiose ideals that technology would free us from the daily grind. Allow us to do more. Instead, we hold a computer in our hand and are available 24/7. No rest for the weary. As we attempt to disentangle ourselves, and focus on coordinated efforts to right twenty years of laissez-faire policy, we can look to the Harris Poll Alienation Index. Want to know what people believe and how to help them help themselves? This is a great place to start. Where Do We Fit? Really. Over the last few years, we’ve focused on diversity and inclusion with a focus on those in the Data industry. But beyond race and gender, there’s a wider gap and the Harris Poll strives to help us understand what’s wrong so we can fix it. After all, isn’t this the basis of why we seek Data? To have the information we need to correct a problem? Data is the new oil. Data Scientists are the next rock stars. These statements and similar filled headlines in the second half of the 2010s. While its true, the question is, what does it mean? Well, it depends. Data is a commodity and when it comes to healthcare, social services, food, and housing, it’s important to have the right information. On the flip side, it can be used to skew feelings further to one side or the other. And that can cause bigger problems. So, the question becomes not ‘can the new decade bring what the last decade missed,’ but ‘what should we be asking and where do we fit, really?’ What the Last Decade Missed Without meaning to, the last decade alienated most of us from the powers that be and from each other. In our excitement to connect, we have 5,000 friends or connections, none of whom we know. Slowly, the norm is building to have “offline meetings” once again. Remember when it was the other way around? Our Data isn’t our own and its only been in recent years, major platforms have attempted to listen. Feelings persist of loneliness, anger, and a sense that no one is listening or cares. Driving the wedge further is class and incentivization. We want to belong. But in our most recent digital world, it’s a ‘pay to play’ belonging. One Final Thought… It may seem as though this has been a disparagement about the digital world. But ultimately, it’s a cautionary tale of the changes which are possible as we enter this new decade. After all, we want to fill the gap the last decade missed and changes are already under way. We have begun to come together much more in the way the digital nation was intended. New startups are paying attention to how people feel and what they want or need. Businesses need soft skills to balance out the technical skills to help with communication across departments and for stakeholders. Can you talk to a UX Designer or Data Engineer as easily as you can talk to an Executive? Can you take a request from an Executive and explain it to your Data Analyst? It’s this flexibility which remains an important skill to focus on the next decade begins. Are you up for the challenge? If so, we may have a role for you. Take a look at our current opportunities or get in touch with one of our expert consultants to learn more: For our West Coast Team, call (415) 614 - 4999 or send an email to email@example.com. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to firstname.lastname@example.org.
09. January 2020
We are in a time in which what we do with Data matters. Over the last few years, we have seen a rapid rise in the number of Data Scientists and Machine Learning Engineers as businesses look to find deeper insights and improve their strategies. But, without proper access to the right Data that has been processed and massaged, Data Scientists and Machine Learning Engineers would be unable to do their job properly. So who are the people who work in the background and are responsible to make sure all of this works? The quick answer is Data Engineers!... or is it? In reality, there are two similar, yet different profiles who can help help a company achieve their Data-driven goals. Data Engineers When people think of Data Engineers, they think of people who make Data more accessible to others within an organization. Their responsibility is to make sure the end user of the Data, whether it be an Analyst, Data Scientist, or an executive, can get accurate Data from which the business can make insightful decisions. They are experts when it comes to data modeling, often working with SQL. Frequently, “modern” Data Engineers work with a number of tools including Spark, Kafka, and AWS (or any cloud provider), whilst some newer Databases/Data Warehouses include Mongo DB and Snowflake. Companies are choosing to leverage these technologies and update their stack because it allows Data teams to move at a much faster pace and be able to deliver results to their stakeholders. An enterprise looking for a Data Engineer will need someone to focus more on their Data Warehouse and utilize their strong knowledge of querying information, whilst constantly working to ingest/process Data. Data Engineers also focus more on Data Flow and knowing how each Data sets works in collaboration with one another. Software Engineers - Data Similar to a Data Engineers, Software Engineers - Data ( who I will refer to as Software Data Engineers in this article) also build out Data Pipelines. These individuals might go by different names like Platform or Infrastructure Engineer. They have to be good with SQL and Data Modeling, working with similar technologies such as Spark, AWS, and Hadoop. What separates Software Data Engineers from Data Engineers is the necessity to look at things from a macro-level. They are responsible for building out the cluster manager and scheduler, the distributed cluster system, and implementing code to make things function faster and more efficiently. Software Data Engineers are also better programers. Frequently, they will work in Python, Java, Scala, and more recently, Golang. They also work with DevOps tools such as Docker, Kubernetes, or some sort of CI/CD tool like Jenkins. These skills are critical as Software Data Engineers are constantly testing and deploying new services to make systems more efficient. This is important to understand, especially when incorporating Data Science and Machine Learning teams. If Data Scientists or Machine Learning Engineers do not have a strong Software Engineers in place to build their platforms, the models they build won’t be fully maximized. They also have to be able to scale out systems as their platform grows in order to handle more Data, while finding ways to make improvements. Software Data Engineers will also be looking to work with Data Scientists and Machine Learning Engineers in order to understand the prerequisites of what is needed to support a Machine Learning model. Which is right for your business? If you are looking for someone who can focus extensively on pulling Data from a Data source or API, before transforming or “massaging” the Data, and then moving it elsewhere, then you are looking for a Data Engineer. Quality Data Engineers will be really good at querying Data and Data Modeling and will also be good at working with Data Warehouses and using visualization tools like Tableau or Looker. If you need someone who can wear multiple hats and build highly scalable and distributed systems, you are looking for a Software Data Engineer. It's more common to see this role in smaller companies and teams, since Hiring Managers often need someone who can do multiple tasks due to budget constraints and the need for a leaner team. They will also be better coders and have some experience working with DevOps tools. Although they might be able to do more than a Data Engineer, Software Data Engineers may not be as strong when it comes to the nitty gritty parts of Data Engineering, in particular querying Data and working within a Data Warehouse. It is always a challenge knowing which type of job to recruit for. It is not uncommon to see job posts where companies advertise that they are looking for a Data Engineer, but in reality are looking for a Software Data Engineer or Machine Learning Platform Engineer. In order to bring the right candidates to your door, it is crucial to have an understanding of what responsibilities you are looking to be fulfilled. That's not to say a Data Engineer can't work with Docker or Kubernetes. Engineers are working in a time where they need to become proficient with multiple tools and be constantly honing their skills to keep up with the competition. However, it is this demand to keep up with the latest tech trends and choices that makes finding the right candidate difficult. Hiring Managers need to identify which skills are essential for the role from the start, and which can be easily picked up on the job. Hiring teams should focus on an individual's past experience and the projects they have worked on, rather than looking at their previous job titles. If you're looking to hire a Data Engineer or a Software Data Engineer, or to find a new role in this area, we may be able to help. Take a look at our latest opportunities or get in touch if you have any questions.
26. September 2019
Privacy and transparency are two sides of the same coin. With the amount of Data we give and companies consume, we want to know our personal information is safe. We want to know we are safe from illegal use of our information. But as conversations about FaceApp, Facebook, Cambridge Analytica, and Google privacy issues make the rounds again, we now know to be much more cautious. Companies would be wise to follow. States Take the Reins to Enact Privacy Rules Though the General Data Protection Regulation (GDPR) passed last year in Europe, businesses in the U.S. have not been so constrained. While there is no overarching federal law, states have taken steps to protect the privacy of their residents and have passed their own Data protection laws. Though all 50 states have enacted notification laws to inform consumers if personal information has been compromised, only California and Vermont have instituted laws requiring businesses to make real change in their Data operations. Other states, from Oregon to Virginia have expanded their definitions of identifying information and increased fines to $500,000 for breaches of privacy. These more stringent rules affect such information as that from Electronic Health Records to tax preparers. And when it comes to Data disposal, companies are required to shred or modify in some way any personal information before tossing it away. Student information is particularly protected in Iowa, in which online efforts against selling their information or otherwise siphoning from online profiles are expressly forbidden by state law. These are just a few of the rules in place and vary slightly from state to state. So, how can you ensure you’re in compliance? Some Tips to Ensure You’re in Compliance If you need to create or amend your Data Management program, here are a few tips to consider: Conduct a gap assessment. What existing procedures are in place which may need to be revised?Ensure your legal teams work closely with your IT, business, and marketing teams to monitor changes and reassess your company’s mitigation controls. How effective are those controls within this legal landscape?Ensure the consumer Data you’re collecting is “critical” to the company. Create a process to receive, review, and fulfil customer requests. But also consider how you handle their information should a customer wish to opt out.Train employees on how to handle personal information. Create and maintain procedures on policy changes and best practices for your Data protection policies. A final note on the above tips, though each state has their own laws, it’s important to consider Golden Rule when it comes to privacy; how would you want your personal information handled? Data is a Commodity. Trust is Valued. Broken promises have tarnished trust in companies. According to a recent survey by SAP, nearly 70% of customers said they don’t trust brands with their personal information. So as companies strive to offer the best customer experience, remember it’s more than flashing lights and deep discounts. Customers want to know their personal Data is safe. So how you ensure this is the case and maintain your customer’s trust? Be transparent. Collect customer information with clear intentions and keep your customers informed of changes to policies. Legal verbiage in policies are to protect companies. It’s time to rethink this strategy and enact policies to protect customers. Though their wariness is warranted, consider how not being transparent and protecting your own business has been detrimental to the customer experience. By being proactive in Data policy compliance laws, you let customers know you’re putting their needs first. That builds trust and loyalty to your business. Isn’t that what every business strives to attain? Even the tech companies realize its import and impact. Earlier this year, tech companies laid out what they’d like to see in federal Data privacy laws. The key takeaway? One set of rules for all is preferred over the slightly differing state laws. If you’re interested in Big Data and Analytics, we may have a role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to email@example.com. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to firstname.lastname@example.org.
25. July 2019
School’s in! Apprenticeships are on the rise within the realm of technology. Demand is so strong, major players like Google and IBM are eschewing traditional education tracks and offering programs for the next generation of Data & Technology professionals. Opensource courses offer opportunities for those in any profession to gain an understanding of Data Science, Big Data, Artificial Intelligence, and more. There is no finite end to education. Technology is changing things at such a rapid pace, we must constantly be learning in order to keep up. Businesses offer graduate schemes and continuing education. To stay ahead, they must invest in themselves, their staff, and just may also be investing in the next generation. What are the implications for AI in schools? To prepare for the future of a blended workforce, schools must begin preparing students now. They must provide environments that couple human creativity with the analytical ability of computers and robots. Of the five major shifts happening with AI in schools, two seem particularly relevant in today’s landscape: Socratic Learning in the Digital Age In today’s world, the teacher becomes less of a lecturer and more of a guide or coach as the students learn in virtual environments. Learning and teaching have become immersive experiences, rather than a tell and retell model. For example, USC Institute for Creative Technologies is prototyping a virtual learning program that combines AI and 3D animation to guide students through learning content and platforms. In this model, students work through a problem together with a teacher only offering support when a student gets hung up. Rather than giving the answer or asking another student, everyone works together to solve the problem, setting the stage for work in their future chosen field. Tearing Down Walls Once the domain of gap and exchange years or peer tutoring, the world can truly be a classroom for all. Through apps, such as Brainly, a social media site for Q & A, users can connect with their peers to answer subject- specific questions. Students are connected are like never before. Think of it as crowd-sourced education, with students working together across the globe. On the flip side, instructors can use AI to help create a more blended learning environment online. Learning ecosystems such as Teachable, Udemy and CourseCraft couple coaching with content acquisition through videos, group chats, editable worksheets and varied assessments. How AI Can Help The focus for years has been on fears that AI will take over jobs. But, with an adaptive mindset that we will always learn as we go, we can begin to embrace AI in both schools and the workplace. AI doesn’t have to scare us. We are still teaching writing, reading, and arithmetic, but in the 21st century classroom we are also learning to write code and analyze data. Although it’s still in its infancy, companies that have managed to incorporate AI are showing impressive results. Companies showing over 20% revenue growth are currently using AI in at least 60% of their operations. Digital leadership is beginning to take root as CEOs start to full appreciate the importance of these new technologies. Not only can AI blend a more immersive learning experience for students in school, it can also help free up humans to be more creative, and has led to job creation in new sectors. In the finance sector, new positions opened up with the introduction of teller machines; including loan specialists, investment advisors, and other more ‘relationship-based’ services. Top employers insist that AI is helping humans spend their time on more creative pursuits and less time on the mundane administrative tasks. If you’re interested in Big Data and analytics, we may have a role for you. We specialize in Junior and Senior roles. Check out our current vacancies or contact us to learn more. For the West Coast Team, please call (415) 614 4999 or email email@example.com. For the Mid-West and East Coast Teams, please call (212) 796 6070 or email firstname.lastname@example.org.
09. October 2018
From coast to coast, a new breed of data analyst rises. No longer siloed and pigeon-holed into one specific area or another, today’s professional must be able to nuance actionable insights for better business predictions and performance. The evolving role of data analyst marries technical prowess and analytical skills with the soft skills of coaching and communication. Every organization from AdTech to FinTech to the Food and Beverage Industries, and every industry in between, depends on data. In fact, by 2020, IBM estimates the number of open positions in the U.S. for data professionals will increase to 2.7 million. Yet, the surge and the shortfall in analytics talent remains as data analyst recruitment efforts rise to the challenge. Broaden Your SkillSet With high demand and short supply comes the opportunity to go beyond your comfort zone and expand your skillset. Add to that companies that may not have the budgets to cover their recruitment efforts and the data analyst skillset must expand to meet the demand. From technical to soft skills, below are a few things to keep in mind when crafting your resume or CV: Don’t shed the basics of analytical mainstays such as Excel, SQL, and SAS; enhance them with languages such as R and Python. Want to boost your chances to the top of the pile? Don’t forget next generation tools and platforms like Tableau, Domo, Adobe Analytics, and/or Snowplow.Be specific: Companies will be more interested in interviewing you if you can clearly outline why/what you have used different technology for.Keep this punchy, concise, and outline your in-put with said technologies.Outline projects you’ve worked on.Become a storyteller – communicate key insights more effectively with the power of data, visualization, and narrative. The ability to tell a story with data can translate across business functions and departments for a unified predictive or prescriptive analysis for more impact.Offer actionable Insights - put the power of actionable insights into decision makers’ hands with real life application explanations. Steward data responsibly. Data governance is now business critical and the new data analyst must be able to act with fiduciary responsibility to ensure data privacy. Data must be protected, standards must be followed, and trust must be maintained I, Meet RobotThe blending of the physical and digital worlds through AI, Machine Learning, and IoT remain the frontrunners in technology through 2020. According to McKinsey’s Report Ten IT-enabled Business Trends for the Decade Ahead, the latest technologies shaping the current business world include automated knowledge work, the mobile platform, and the Cloud. Skillsets and experience within these three technologies are the next wave in the modern digital world and it’s the new breed of data analyst who can best rise to the challenge to fill the gaps.Not only will these three technologies make an impact, but the impetus of social platforms and their data will be a powerful contribution to business outcomes. This melding of the physical and digital worlds allows businesses to understand and implement the collected data in scenarios in real-time driving them forward to better reward.Your TurnIn this section, we ask our candidates and clients what we as recruiters can do to help you find the perfect fit. This is your chance to answer and ask questions as well as get creative in helping us improve our efforts in data analyst recruitment. Below are a few questions to get you started.What kind of cross-training programs might businesses and schools employ for future Data Analysts?What other backgrounds are we overlooking in our quest to for the next generation of data analyst as businesses seek to find and engage this most critical role within their data teams?What can we, as recruiters do to engage qualified candidates ready for their next role in the world of data and analytics? If you’re a data analyst ready to spread your wings, we may have a role for you, check out our current vacancies or contact us to learn more.For the East Coast and Mid-West teams please call 212-796-6070, or email email@example.com.For the West Coast team call 415-614-4999 or email firstname.lastname@example.org.
09. May 2018
Last week, we reviewed a few highlights from 2017. One of those highlights was the IoT of healthcare. In the conclusion of our 2-part series, we’ll take a look at a few tech trends for 2018 and their impact on the growing digital technology within the healthcare industry. As the population ages, it’s important to form ranks, consolidate information, and utilize insights from big data and analytics for improved healthcare.Healthcare systems across the country are feeling the pinch to consolidate and work together to provide improved healthcare to their patients regardless of the political climate and San Francisco is no exception. San Francisco boasts a thriving economy and in a region often segmented by its marketplaces, healthcare organizations are coming together as independent hospitals get folded into larger systems or disappear altogether. Combined with the biggest driver of change – consumer demand – healthcare is just one of the industries poised to welcome digital technology to its doors. What better way to provide improved services and manage expenses across health systems?Business Intelligence is Critical to HealthcareHospital and Healthcare systems are complex warehouses utilizing vast amounts of data to support operations and provide patient care. As data sources increase, healthcare organizations must keep up and with advanced analytics to support decision-making capabilities, they can. Data visualization tools, predictive modeling, and business intelligence software applications can help organizations gain insight to ensure best practices are in play, but also patient satisfaction, clinical operations, and administration and management hum like the well-oiled machine they are to continuously improve services.Elevating care throughout all departments and becoming a value-based organization can only be achieved through the intelligent application of data-derived insights obtained thanks to comprehensive, advanced BI software.Deriving Value from Healthcare AnalyticsPredictive modeling and data visualization are key components in deriving value from healthcare analytics, though central to BI users understanding of information received, helps process patient data insights. Applying insights to vital areas of patient care, hospital management and operation, help to answer the questions “why” and “what will happen in the future”, rather than the formerly reactionary “what happened”.Healthcare dashboards offer simple, streamlined, and efficient business intelligence to help leverage data for improved services and care. Patient-related insights are crucial to making this happen. Using advanced analytics, healthcare institutions have the power to ask important questions about the future to inform their decision-making. The ability to ask the important questions allows healthcare management to take proactive steps towards preventative treatment in real-time to provide the best care for their patients. On the Cutting Edge – Tech Trends for Healthcare and Across IndustriesElectronic Healthcare Records Management (EHRM), wearable devices, digital medicine, and cutting edge applications are just a few of a long list of the Internet of Things (IoT) in healthcare. Spurred by innovations in edge devices such as intelligent routers, gateway servers, and device firmware, computer power has shifted IoT computing to the edge. This trend will improve processes and further engage customers leading to immersive experiences. Imagine not only tracking your heart rate, but receiving an EKG in real-time, right from your watch. No trip to the doctor’s office required.Machine learning is on the rise as AI technologies help software systems learn on their own. Improvements in AI technologies, particularly in regard to speech analytics, natural language progression, and deep-learning platforms have firms poised to scale their businesses more efficiently as software learns to adapt without programming.As technology advances, humans are increasingly found working side-by-side with software robots. Yet, robots are not pushing humans out of the workforce as once imagined. Though repeatable tasks such as search, collate, update, and access multiple systems are some of the jobs being automated, it’s estimated 25 percent of jobs will be transformed through the advent of social machines. This move in social machines is where robot software meets human interaction for increased opportunities.If you’re interested in bringing your big data skills to healthcare, we may have a role for you. We’re currently recruiting for a Senior Data Engineer (Remote) or check out our other vacancies.For the East Coast and Mid-West teams please call 212-796-6070, or email email@example.com.For the West Coast team call 415-614-4999 or email firstname.lastname@example.org.
17. January 2018